Fieldwork funded by the D M McDonald Grants and Awards Fund!

Excited to announce that the D M McDonald Grants and Awards Fund has agreed to fund my fieldwork this summer to the Neanderthal Rock Shelter site of Le Rozel in France. This site has previously unearthed a large collection of adult and children Neanderthal footprints (read all about it here). I was last on site in 2018 and the site is absolutely amazing! I’ll be heading back this summer to assist in further excavations but also to conduct a few biomechanical analyses in collaboration with Dr Dominique Cliquet… stay tuned for more information later this year!

(time to download DuoLingo to improve my French!)

Our new paper from the DAWNDINOS project on evolutionary biomechanics in dinosaurs and archosaurs is just out !

Cuff, A.R., Demuth, O.E., Michel, K., Otero, A., Pintoire, R., Polet, D., Wiseman*, A.L.A., Hutchinson, J.R. 2022. Walking—and Running and Jumping—with Dinosaurs and Their Cousins, Viewed Through the Lens of Evolutionary Biomechanics. Integrative and Comparative Biology.

Read all about it here

The latest paper from DAWNDINOS just landed – this is the project where I completed my first postdoc on evolutionary biomechanics of archosaurs. Our new paper – a big team effort from everyone – provides a lovely overview into the locomotory superiority hypothesis and what our team during the 5.5year long project accomplished! Which, of course, provides an insight into biomechanical modelling of extant and extinct species, some beautiful phylogenies and how we can test how an extinct species may have moved (such as estimating gait from footprints!)

Is this the end of DAWNDINOS? Yes and no. The project officially ended in March 2022 (boo!), but we still have lots more data and analyses in the pipeline, so keep your eyes and ears posted for announcements on future publications 🙂

New skeletal reconstruction of Euparkeria capensis by Oliver Demuth

Our new paper is just out in Scientific Reports: 3D polygonal muscle modelling and line of action estimation in living and extinct taxa

Or: how to recontruct soft tissues in living and extinct animals!

Reconstructed 3D polygonal muscles of the extinct Eupakeria capenensis. B shows the estinated line of action (LOA) of each muscle. These LOAs are used in biomechanical modelling.

Our co-authored paper was just published in Scientific Reports, led by Oliver E. Demuth as part of the DAWNDINOS project, led by Professor John R. Hutchinson. Find the paper here

Abstract: Biomechanical models and simulations of musculoskeletal function rely on accurate muscle parameters, such as muscle masses and lines of action, to estimate force production potential and moment arms. These parameters are often obtained through destructive techniques (i.e., dissection) in living taxa, frequently hindering the measurement of other relevant parameters from a single individual, thus making it necessary to combine multiple specimens and/or sources. Estimating these parameters in extinct taxa is even more challenging as soft tissues are rarely preserved in fossil taxa and the skeletal remains contain relatively little information about the size or exact path of a muscle. Here we describe a new protocol that facilitates the estimation of missing muscle parameters (i.e., muscle volume and path) for extant and extinct taxa. We created three-dimensional volumetric reconstructions for the hindlimb muscles of the extant Nile crocodile and extinct stem-archosaur Euparkeria, and the shoulder muscles of an extant gorilla to demonstrate the broad applicability of this methodology across living and extinct animal clades. Additionally, our method can be combined with surface geometry data digitally captured during dissection, thus facilitating downstream analyses. We evaluated the estimated muscle masses against physical measurements to test their accuracy in estimating missing parameters. Our estimated muscle masses generally compare favourably with segmented iodine-stained muscles and almost all fall within or close to the range of observed muscle masses, thus indicating that our estimates are reliable and the resulting lines of action calculated sufficiently accurately. This method has potential for diverse applications in evolutionary morphology and biomechanics

Okay… but how do you do that?

Well, first you identify the muscle’s origin and insertion. Then, follow the steps in the supplementary information using AUTODESK MAYA (free for researchers/academics/education purposes) to create a polygonal muscle, which uses a closed cylinder approach with either 8, 12 or 16 faces to describe the circumference. The cylinder’s height is arbitrarily defined depending on muscle body length. The cylinder follows the muscle’s path, as shown below for Euparkeria.

The end result is a polygon representing the volume, shape and size of a given muscle. If you wish to move beyond soft tissue reconstruction, then you can also run the provided line of action (LOA) estimation script in MAYA (uses MAYA EMBEDDED LANGUAGE) which generates a LOA, threaded through the midline of the body.

But… how do you choose the muscle path and configuration?

Well, there’s a few methods you could use! For the above, we used cross-sections of an alligator’s leg (an analagous species to Euparkeria). These cross sections helped to guide the muscle’s path and volume (see figure below) and made sure that each reconstructed muscle stayed within its boundary and reflected reality.

For living species, you can use the above method too, or instead use CT or MRI scans to guide muscle configurations, but you could also use surface scans of muscle layers! The latter is not only cheaper, but also helps to streamline the muscle modelling approach in which the user can:

(1) Collect dissection data

(2) Surface scan each topographical layer during dissection (alternatively, you could also use photogrammetry, which can be done cheaply using a smartphone with an in-built camera and free online photogrammetry software – see this wonderful blog by Dr Peter Falkingham for how-to guides and an overview of software)

(3) Use the surface scans to guide muscle paths/LOA estimation

(4) Build a subject-specific model in which dissection data AND muscle path data comes directly from the same specimen

We tried this approach on the shoulder musculature of a gorilla, as shown below.

Left: shoulder musculature of a gorilla and estimated LOAs. Middle: polygonal muscle modelling approach of the gorilla surface scan data. Right: cross-section of alligator hindlimb muscles.

After this process, the soft tissues of the desired body segment (here, limbs) will be reconstructed! Below, we have the 3D reconstructed hindlimb and pelvic muscles of Euparkeria (see our paper for muscle abbreviations). And why would we want to do something like this? Other than it looking pretty cool, of course! For future biomechanical modelling studies… watch this space! 🙂

New paper published: A Guide to Inverse Kinematic Marker-Guided Rotoscoping using IK Solvers

Our new paper just landed in Integrative Organismal Biology. Go check it out here

*Copyedit version expected mid Feb 2022

This paper forms a part of my previous postdoc on the DAWNDINOS project in which we collected motion data of crocodiles using biplanar X-ray, also known as ‘XROMM’ (X-ray Reconstruction of Moving Morphology). This method involves taking a series of X-ray snapshots from at least two different angles/positions whilst an animal/object moves through a designated capture area. From this, you compile a video of the X-rays in which you can then see skeletal movement! It is pretty cool.

We placed tantalum markers inside the hindlimb of a crocodile which are quite dense and show up very well on the X-ray shadows (see the image below and try to look for black circles on the limb bones – those are the markers). These markers get tracked throughout a motion and we use those marker positions/trajectories to guide movement of the bones. For example, if the 3D position of these markers moves over there, then the respective bone on which they are attached to moves over there too.

It all sounds pretty straight forward in theory. In practise, things can go wrong during the initial setup. To place markers in the hindlimb, you first need to perform minor surgery on the animal. It’s not so simple to get straight down to the bone during surgery – there’s a lot of soft tissue in the way. And – so – mistakes happen. Sometimes beads can be misplaced, or become ‘lost’ in the body. All beads might be thought to have been successfully placed, but during the animal’s recovery period, the bead can travel elsewhere in the body! Imagine my frustration when I was tracking the XROMM data to discover that one crocodile was missing a critical bead placement in the pelvis, despite being placed in the correct position during surgery! And we only know when this happens after experimentation (which may even be after you have lost access to the animal so no further surgery and experimentation can happen). Prior to this discovery of the ‘lost’ bead, we had already established the IK rig and had tracked more than 50 trials in another animal. So this really threw a spanner in the works. Would we need to re-invent the tracking wheel? Was all data from that crocodile useless? What could we do?

And this is where our paper comes into play. What do you do when this happens? Is all lost? Is all motion data from that animal useless? Not quite!! Of course, the following will depend on the research question at hand and the intended use of the data. But if you are tracking data to be used in musculoskeletal modelling with the intention of limiting degrees of freedom, then you can use the method we have called ‘inverse kinematic (IK) marker-guided rotoscoping’*. See the below diagram to see how this method compares with other methods, such as scientific rotoscoping:

*this is because our method loses some anatomical fidelity, but may be of little to no concern for certain types of biomechanical studies

Our method combines inverse kinematic solvers with that of traditional scientific rotoscoping methods to quickly and efficiently overlay 3D bone meshes with the X-ray shadows from XROMM data. We demonstrate this method using a case study of three Nile crocodiles’ (Crocodylus niloticus) forelimbs and hindlimbs. Within these limbs, different marker configurations were used: some configurations had six markers, others had five markers and all forelimb data only had three markers*. To evaluate IK marker-guided rotoscoping, we systematically removed markers in the six-marker configuration and then tested the magnitudes of deviation in translations and rotations of the rigged setup with fewer markers versus those of the six-marker configuration. We established that IK marker-guided rotoscoping is a suitable method for ‘salvaging’ data which may have too few markers.

*The three marker configuration definitely turned out to be a bit of a headache to solve. Co-first author Oliver Demuth came up with the idea of using another IK rig controlling the first to track these trials

We illustrate how each of these setups is implemented in Autodesk Maya below:

The result of all rigs (hindlimbs and forelimbs) was a set of XROMM-informed bony motions from which the rotations of each joint and the translations and rotations of the pelvic/pectoral girdles were exported. These translations and rotations can be used to animate musculoskeletal models or conduct simulations from which we can extract biomechanical information.

Below we illustrate how accurately the different marker configurations compare to the original setup. If the tracking was perfect, then all colours would align perfectly. But we can see that there is some small deviation in the tracking which was negligible for our previous study published last year in Journal of Anatomy (check that out here):

Please check out the paper to see how the method might be useful for you. Step by step instructions can be found in the supplementary material. We also provide the Maya 2019 file (.ma) which you can use as a template to set up your own IK rig in Maya.